Lead Artificial Intelligence Researcher, Programming Systems Research, Intel Labs
Steering Committee Chair, Machine Learning and Programming Languages Workshop
Chair, Industrial Board for PRECISE Center, University of Pennsylvania
Executive Director of AI Research and Development, PRECISE Center for Safe AI, University of Pennsylvania
Principal Investigator and Co-Founder, Intel/NSF CAPA Research Center
TheWebConf'20 (Intelligent Systems and Infrastructure Track), MAPL'20 (SC chair), SysML'20, PACT'19 (SRC), SysML'19, MAPL'18 (general chair), MAPL'17 (program chair)
At Intel Labs, I am the lead artificial intelligence researcher for programming systems research and the principal investigator and co-founder of the joint Intel/NSF CAPA research center. In academia, I have appointments as the executive director of AI research and development for the PRECISE Center for Safe AI at the University of Pennsylvania and as the chair of the PRECISE industrial advisory board.
Overall, I perform research in artificial intelligence with a focus on machine programming, anomaly detection, deep learning, and autonomous systems. I try to build and maintain deep academic and industrial ties. I'm wildly interested in machine programming. In 2016, I co-founded the machine learning and programming languages (MAPL) workshop and was its program and general chair in 2017 and 2018, respectively. In 2019, I accepted the invitation as the chair of the MAPL steering committee.
I am an adjunct professor at the University of Colorado-Boulder and a lecturer at the University of Pennsylvania on anomaly detection for safe autonomy. I was previously the director of engineering at Machine Zone, where I oversaw the engineering of Game of War and Mobile Strike. When not doing research, I work on my online gaming software company, Nodeka, LLC, which I founded in 1999.
My (somewhat dated) CV is here. I have over 60 peer reviewed publications and issued patents with around 100 patents pending. I've given several dozen invited research presentations at places like Berkeley, BMW, IBM Research, Penn, Stanford, VMWare, UCLA, and UW.
Patent issued: "Compute optimization mechanism for deep neural networks" (10,417,734)
Patent issued: "Compute optimization mechanism for deep neural networks" (10,417,731)
Accepted to NeurIPS: "A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions"
Opening address for Machine Programming Day @ Berkeley: "Intel's Machine Programming Pioneering Research Vision"
Accepted invitation as chair of MAPL steering committee.
Q2 Intel Labs' Eureka Award Winner (inventor with most patent applications filed in a quarter (30 new filings)).
Accepted invitation to serve on SysML 2020 program committee.
Patent issued (milestone, 25th issued patent): "Autonomous vehicle advanced sensing and response"
Intel's Annual Gordon Moore Award Nomination: "Informed risk-taking across Intel Labs, PSG, SSG, and University Research that has furthered Intel's FPGA innovations"
- Category: Excellence in Risk Taking.
- Team: Aravind Dasu, Mahesh Iyer, Eriko Nurvitadhi, Michael Adler, Justin Gottschlich, Mondira Pant, Todd Younkin
Intel Tech Insights Leadership Award: "Machine Programming: A Radical Approach to Automating Software" (Justin Gottschlich and Tim Mattson)
Patent issued: "Extend GPU/CPU coherency to multi-GPU cores"
DATSA has been open sourced.
SysML whitepaper: "SysML: The New Frontier of Machine Learning Systems"
Patent issued: "Detecting root causes of use-after-free memory errors"
Invited talk to Dawn Song's research team at Berkeley: "Anomaly detection, machine programming, and other AI research at Intel"
Co-teaching with Insup Lee and James Weimer: CIS 700-002: Topics in Safe Autonomy, Spring 2019
PhD co-advisor: Irina Calciu, Brown University - VMWare
PhD committee member: Wenjia Ruan, Lehigh University - Qualcomm
PhD committee member: Mohammad Mejbah ul Alam - Intel Labs